example works now

.gitignore

 .Rproj.user
 .Rhistory
-README.rmd
+

README.Rmd

+---
+output: github_document
+---
+
+<!-- README.md is generated from README.Rmd. Please edit that file -->
+
+```{r options, include = FALSE}
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>",
+  fig.path = "man/figures/README-",
+  out.width = "100%"
+)
+```
+
+# simulateDCE
+
+<!-- badges: start -->
+
+<!-- badges: end -->
+
+The goal of simulateDCE is to make it easy to simulate choice experiment datasets using designs from NGENE or `spdesign`. You have to store the design file in a subfolder and need to specify certain parameters and the utility functions for the data generating process. The package is useful for
+
+1.  Test different designs in terms of statistical power, efficiency and unbiasedness
+
+2.  To test the effects of deviations from RUM, e.g. heuristics, on model performance for different designs.
+
+3.  In teaching, using simulated data is useful, if you want to know the data generating process. It helps to demonstrate Maximum likelihood and choice models, knowing exactly what you should expect.
+
+4.  You can use simulation in pre-registration to justify your sample size and design choice.
+
+5.  Before data collection, you can use simulated data to estimate the models you plan to use in the actual analysis. You can thus make sure, you can estimate all effects for given sample sizes.
+
+## Installation
+
+You can install the development version of simulateDCE from gitlab. You need to install the `remotes` package first. The current version is alpha and there is no version on cran:
+
+``` r
+
+install.packages("remotes")
+remotes::install_gitlab(repo = "dj44vuri/simulateDCE" , host = "https://git.idiv.de")
+```
+
+## Example
+
+This is a basic example for a simulation:
+
+```{r example}
+ library(simulateDCE)
+library(rlang)
+library(formula.tools)
+
+# Designpath indicates the folder where all designs that should be simulated are stored. Can be either ngd files (for NGENE) or R objects for spdesign)
+designpath<- system.file("extdata","SE_DRIVE" ,package = "simulateDCE")
+
+# on your computer, it would be something like
+# designpath <- "c:/myfancyDCE/Designs"
+
+
+# number of respondents
+resps =120
+
+# number of simulations to run (about 200 is minimum if you want to be serious -- but it takes some time. always test your code with 2 simulations, and if it runs smoothly, go for more.)
+nosim= 2 
+
+# If you want to use different groups of respondents, use this. The following line means that you have one group of 70% size and one group of 30% size
+decisiongroups=c(0,0.7,1)
+
+# set the values of the parameters you want to use in the simulation
+bpreis = -0.01
+blade = -0.07
+bwarte = 0.02
+
+# If you want to do some manipulations in the design before you simulate, add a list called manipulations. Here, we devide some attributes by 10
+
+manipulations = list(alt1.x2=     expr(alt1.x2/10),
+                     alt1.x3=     expr(alt1.x3/10),
+                     alt2.x2=     expr(alt2.x2/10),
+                     alt2.x3=     expr(alt2.x3/10)
+)
+
+
+#place your utility functions here. We have two utility functions and two sets of utility functions. This is because we assume that 70% act according to the utility u1 and 30% act to the utility u2 (that is, they only decide according to the price and ignore the other attributes)
+u<-list( u1 =
+
+           list(
+             v1 =V.1~  bpreis * alt1.x1 + blade*alt1.x2 + bwarte*alt1.x3   ,
+             v2 =V.2~  bpreis * alt2.x1 + blade*alt2.x2 + bwarte*alt2.x3
+           )
+
+         ,
+         u2 = list(  v1 =V.1~  bpreis * alt1.x1    ,
+                     v2 =V.2~  bpreis * alt2.x1)
+
+)
+
+# specify the designtype "ngene" or "spdesign"
+destype="ngene"
+
+
+#lets go
+sedrive <- sim_all()
+
+```